In the past, in order to perform classification of the chemical states of biological samples including many types of molecules, or concentration estimation (calibration) of components included in the biological samples, a method of a multivariate analysis (chemometrics) has been adopted in which vibrational spectra (Raman spectra or infrared absorption spectra) of a biological sample are acquired, and intensity information of the entire frequency region in the acquired vibrational spectra is treated as a variate (see, for example, U.S. Pat. No. 6,341,257).
According to such a method of chemometrics, vibrational bands (Raman bands or infrared absorption bands) given by each component included in the biological sample are superimposed on the spectrum. Therefore, as long as a frequency domain having a low correlation between spectral profiles given by each component exists in the acquired vibrational spectrum even when the vibrational spectrum of the sample exhibits an intensity pattern (spectral profile) of a complex spectrum, it is possible to perform calibration or classification of the chemical states of the biological sample on the basis of information of the vibrational spectrum.
Specifically, since nucleic acid and protein included in the biological sample are significantly different in chemical composition or molecular structure, the correlation of the spectral profile between the vibrational spectra is low. Alternatively, in a plurality of types of proteins included in the biological sample, when there is a significant difference in the frequency of appearance of a specific amino-acid side chain or in the steric structure (secondary structure or tertially structure), the correlation of the spectral profile between the vibrational spectra of these proteins also becomes low.
In the biological sample to be analyzed, when the types or the relative amounts of such a component (molecule) having a low correlation of the spectral profile fluctuates for each sample, it is possible to classify the states of the sample from distribution of the score plot (PCA score plot) of a principle component by executing principle component analysis (Principle Component Analysis, hereinafter, referred to as the PCA) with respect to the vibrational spectra. In addition, it is also possible to estimate the concentration of the component included in the sample by creating a calibration curve on the basis of the vibrational spectra of a reference sample.
In chemometrics, the calibration curve is created by calculating a calibration matrix, and as an algorithm for calculating the calibration matrix, a CLS (Classical Least Squares Fitting) method and an ILS (Inverse Least Squares Fitting) method in which the result of the PCA is not used, and a PCR (Principle Component Regression) method and a PLS (Partial Least Squares Fitting) method which are based on the PCA result (PCA score value) are adopted.